Pathway Summary

Consort map

Demographic information

Characteristic

N

Overall, N = 1401

control, N = 711

treatment, N = 691

p-value2

age

138

50.91 ± 12.56 (25 - 74)

51.44 ± 12.37 (25 - 74)

50.37 ± 12.82 (28 - 73)

0.620

Unknown

2

2

0

gender

140

0.916

f

107 (76%)

54 (76%)

53 (77%)

m

33 (24%)

17 (24%)

16 (23%)

occupation

140

0.641

day_training

2 (1.4%)

2 (2.8%)

0 (0%)

full_time

17 (12%)

8 (11%)

9 (13%)

homemaker

12 (8.6%)

5 (7.0%)

7 (10%)

other

2 (1.4%)

0 (0%)

2 (2.9%)

part_time

25 (18%)

12 (17%)

13 (19%)

retired

38 (27%)

19 (27%)

19 (28%)

self_employ

7 (5.0%)

4 (5.6%)

3 (4.3%)

student

2 (1.4%)

0 (0%)

2 (2.9%)

t_and_e

2 (1.4%)

1 (1.4%)

1 (1.4%)

unemploy

33 (24%)

20 (28%)

13 (19%)

marital

140

0.817

cohabitation

1 (0.7%)

0 (0%)

1 (1.4%)

divore

15 (11%)

10 (14%)

5 (7.2%)

in_relationship

4 (2.9%)

2 (2.8%)

2 (2.9%)

married

39 (28%)

20 (28%)

19 (28%)

none

70 (50%)

33 (46%)

37 (54%)

seperation

3 (2.1%)

2 (2.8%)

1 (1.4%)

widow

8 (5.7%)

4 (5.6%)

4 (5.8%)

edu

140

0.249

bachelor

35 (25%)

13 (18%)

22 (32%)

diploma

26 (19%)

17 (24%)

9 (13%)

hd_ad

4 (2.9%)

3 (4.2%)

1 (1.4%)

postgraduate

12 (8.6%)

5 (7.0%)

7 (10%)

primary

9 (6.4%)

3 (4.2%)

6 (8.7%)

secondary_1_3

16 (11%)

9 (13%)

7 (10%)

secondary_4_5

32 (23%)

19 (27%)

13 (19%)

secondary_6_7

6 (4.3%)

2 (2.8%)

4 (5.8%)

fam_income

140

0.981

10001_12000

6 (4.3%)

2 (2.8%)

4 (5.8%)

12001_14000

7 (5.0%)

3 (4.2%)

4 (5.8%)

14001_16000

7 (5.0%)

3 (4.2%)

4 (5.8%)

16001_18000

4 (2.9%)

2 (2.8%)

2 (2.9%)

18001_20000

6 (4.3%)

4 (5.6%)

2 (2.9%)

20001_above

27 (19%)

15 (21%)

12 (17%)

2001_4000

20 (14%)

11 (15%)

9 (13%)

4001_6000

14 (10%)

6 (8.5%)

8 (12%)

6001_8000

12 (8.6%)

7 (9.9%)

5 (7.2%)

8001_10000

10 (7.1%)

4 (5.6%)

6 (8.7%)

below_2000

27 (19%)

14 (20%)

13 (19%)

medication

140

123 (88%)

62 (87%)

61 (88%)

0.845

onset_duration

137

15.23 ± 10.25 (0 - 56)

15.87 ± 10.92 (0 - 56)

14.55 ± 9.51 (0 - 35)

0.452

Unknown

3

0

3

onset_age

135

35.90 ± 13.95 (10 - 65)

35.40 ± 12.70 (10 - 61)

36.42 ± 15.23 (14 - 65)

0.673

Unknown

5

2

3

1Mean ± SD (Range); n (%)

2Two Sample t-test; Pearson's Chi-squared test; Fisher's exact test

Measurement

Table

Characteristic

N

Overall, N = 1401

control, N = 711

treatment, N = 691

p-value2

recovery_stage_a

140

3.20 ± 1.18 (1 - 5)

3.27 ± 1.23 (1 - 5)

3.13 ± 1.12 (1 - 5)

0.492

recovery_stage_b

140

17.97 ± 2.78 (8 - 24)

17.90 ± 2.93 (8 - 24)

18.04 ± 2.64 (13 - 24)

0.764

ras_confidence

140

30.03 ± 5.14 (15 - 45)

29.83 ± 4.88 (15 - 40)

30.23 ± 5.42 (18 - 45)

0.646

ras_willingness

140

11.79 ± 2.09 (5 - 15)

11.66 ± 2.07 (5 - 15)

11.93 ± 2.12 (7 - 15)

0.455

ras_goal

140

17.39 ± 3.09 (11 - 25)

17.14 ± 2.89 (11 - 24)

17.64 ± 3.28 (11 - 25)

0.343

ras_reliance

140

13.20 ± 2.95 (5 - 20)

12.99 ± 2.81 (5 - 18)

13.42 ± 3.08 (7 - 20)

0.385

ras_domination

140

9.92 ± 2.42 (3 - 15)

10.17 ± 2.32 (3 - 15)

9.67 ± 2.51 (3 - 15)

0.221

symptom

139

29.94 ± 9.39 (14 - 56)

29.93 ± 9.61 (14 - 55)

29.94 ± 9.23 (15 - 56)

0.994

Unknown

1

0

1

slof_work

140

22.51 ± 4.78 (10 - 30)

22.85 ± 4.38 (13 - 30)

22.17 ± 5.16 (10 - 30)

0.408

slof_relationship

140

25.20 ± 6.03 (9 - 35)

24.90 ± 6.05 (9 - 35)

25.51 ± 6.05 (11 - 35)

0.555

satisfaction

140

20.58 ± 7.23 (5 - 35)

19.99 ± 6.80 (5 - 33)

21.19 ± 7.65 (5 - 35)

0.327

mhc_emotional

140

10.94 ± 3.81 (3 - 18)

10.69 ± 3.69 (3 - 17)

11.20 ± 3.95 (3 - 18)

0.428

mhc_social

140

15.08 ± 5.61 (5 - 30)

14.75 ± 5.59 (5 - 30)

15.42 ± 5.66 (5 - 29)

0.480

mhc_psychological

140

21.94 ± 6.48 (6 - 36)

21.80 ± 6.11 (7 - 36)

22.09 ± 6.88 (6 - 36)

0.796

resilisnce

140

16.69 ± 4.72 (6 - 30)

16.25 ± 4.20 (6 - 24)

17.13 ± 5.20 (6 - 30)

0.274

social_provision

140

13.56 ± 2.89 (5 - 20)

13.11 ± 2.65 (5 - 20)

14.03 ± 3.07 (5 - 20)

0.060

els_value_living

140

16.96 ± 3.17 (5 - 25)

16.59 ± 2.94 (6 - 22)

17.35 ± 3.37 (5 - 25)

0.159

els_life_fulfill

140

12.75 ± 3.44 (4 - 20)

12.37 ± 3.28 (5 - 19)

13.14 ± 3.59 (4 - 20)

0.182

els

140

29.71 ± 6.01 (9 - 45)

28.96 ± 5.53 (11 - 38)

30.49 ± 6.42 (9 - 45)

0.131

social_connect

140

26.46 ± 9.51 (8 - 48)

26.73 ± 9.24 (8 - 48)

26.19 ± 9.84 (8 - 48)

0.736

shs_agency

140

14.36 ± 5.17 (3 - 24)

13.97 ± 4.77 (3 - 21)

14.77 ± 5.57 (3 - 24)

0.365

shs_pathway

140

16.06 ± 4.06 (4 - 24)

15.75 ± 3.87 (5 - 24)

16.39 ± 4.25 (4 - 24)

0.349

shs

140

30.43 ± 8.84 (7 - 48)

29.72 ± 8.27 (8 - 45)

31.16 ± 9.40 (7 - 48)

0.337

esteem

140

12.61 ± 1.65 (9 - 20)

12.65 ± 1.62 (9 - 18)

12.58 ± 1.68 (10 - 20)

0.808

mlq_search

140

14.84 ± 3.52 (3 - 21)

14.70 ± 3.32 (6 - 21)

14.97 ± 3.74 (3 - 21)

0.656

mlq_presence

140

13.51 ± 4.21 (3 - 21)

13.38 ± 3.80 (4 - 21)

13.65 ± 4.63 (3 - 21)

0.704

mlq

140

28.35 ± 6.94 (6 - 42)

28.08 ± 6.26 (10 - 40)

28.62 ± 7.61 (6 - 42)

0.648

empower

140

19.29 ± 4.28 (6 - 30)

18.97 ± 4.17 (11 - 30)

19.61 ± 4.40 (6 - 30)

0.380

ismi_resistance

140

14.55 ± 2.53 (5 - 20)

14.48 ± 2.21 (10 - 20)

14.62 ± 2.84 (5 - 20)

0.737

ismi_discrimation

140

11.59 ± 3.15 (5 - 20)

11.96 ± 3.02 (5 - 20)

11.22 ± 3.26 (5 - 20)

0.165

sss_affective

140

9.92 ± 3.55 (3 - 18)

10.03 ± 3.51 (3 - 18)

9.81 ± 3.60 (3 - 18)

0.719

sss_behavior

140

9.66 ± 3.77 (3 - 18)

9.89 ± 3.85 (3 - 18)

9.43 ± 3.70 (3 - 18)

0.480

sss_cognitive

140

8.19 ± 3.74 (3 - 18)

8.24 ± 3.77 (3 - 18)

8.14 ± 3.73 (3 - 18)

0.882

sss

140

27.78 ± 10.21 (9 - 54)

28.15 ± 10.26 (9 - 54)

27.39 ± 10.22 (9 - 54)

0.660

1Mean ± SD (Range)

2Two Sample t-test

Plot

## Warning: Removed 2 rows containing non-finite values (`stat_density()`).
## Warning: Removed 1 rows containing missing values (`geom_vline()`).

## Warning: Removed 1 rows containing non-finite values (`stat_density()`).
## Removed 1 rows containing missing values (`geom_vline()`).

Data analysis

Table

Group

Characteristic

Beta

SE1

95% CI1

p-value

recovery_stage_a

(Intercept)

3.27

0.138

3.00, 3.54

group

control

—

—

—

treatment

-0.137

0.196

-0.522, 0.248

0.486

time_point

1st

—

—

—

2nd

0.000

0.228

-0.446, 0.446

0.999

group * time_point

treatment * 2nd

0.491

0.327

-0.150, 1.13

0.137

Pseudo R square

0.017

recovery_stage_b

(Intercept)

17.9

0.340

17.2, 18.6

group

control

—

—

—

treatment

0.142

0.485

-0.808, 1.09

0.770

time_point

1st

—

—

—

2nd

-0.377

0.528

-1.41, 0.657

0.477

group * time_point

treatment * 2nd

0.802

0.759

-0.686, 2.29

0.294

Pseudo R square

0.008

ras_confidence

(Intercept)

29.8

0.619

28.6, 31.0

group

control

—

—

—

treatment

0.401

0.881

-1.33, 2.13

0.650

time_point

1st

—

—

—

2nd

0.695

0.735

-0.747, 2.14

0.348

group * time_point

treatment * 2nd

1.12

1.059

-0.954, 3.20

0.294

Pseudo R square

0.018

ras_willingness

(Intercept)

11.7

0.249

11.2, 12.1

group

control

—

—

—

treatment

0.266

0.355

-0.429, 0.961

0.455

time_point

1st

—

—

—

2nd

-0.480

0.299

-1.07, 0.107

0.114

group * time_point

treatment * 2nd

0.691

0.431

-0.154, 1.54

0.114

Pseudo R square

0.018

ras_goal

(Intercept)

17.1

0.376

16.4, 17.9

group

control

—

—

—

treatment

0.497

0.535

-0.552, 1.55

0.354

time_point

1st

—

—

—

2nd

-0.460

0.487

-1.41, 0.495

0.349

group * time_point

treatment * 2nd

1.57

0.701

0.193, 2.94

0.029

Pseudo R square

0.035

ras_reliance

(Intercept)

13.0

0.348

12.3, 13.7

group

control

—

—

—

treatment

0.434

0.495

-0.536, 1.41

0.382

time_point

1st

—

—

—

2nd

0.335

0.397

-0.443, 1.11

0.402

group * time_point

treatment * 2nd

1.04

0.572

-0.077, 2.17

0.073

Pseudo R square

0.037

ras_domination

(Intercept)

10.2

0.282

9.62, 10.7

group

control

—

—

—

treatment

-0.502

0.401

-1.29, 0.284

0.212

time_point

1st

—

—

—

2nd

-0.314

0.416

-1.13, 0.501

0.453

group * time_point

treatment * 2nd

1.42

0.599

0.248, 2.60

0.021

Pseudo R square

0.023

symptom

(Intercept)

29.9

1.117

27.7, 32.1

group

control

—

—

—

treatment

0.012

1.598

-3.12, 3.14

0.994

time_point

1st

—

—

—

2nd

-0.367

1.073

-2.47, 1.74

0.733

group * time_point

treatment * 2nd

-1.18

1.546

-4.21, 1.85

0.447

Pseudo R square

0.003

slof_work

(Intercept)

22.8

0.565

21.7, 24.0

group

control

—

—

—

treatment

-0.671

0.804

-2.25, 0.905

0.405

time_point

1st

—

—

—

2nd

-0.344

0.637

-1.59, 0.904

0.591

group * time_point

treatment * 2nd

0.461

0.918

-1.34, 2.26

0.617

Pseudo R square

0.004

slof_relationship

(Intercept)

24.9

0.708

23.5, 26.3

group

control

—

—

—

treatment

0.606

1.008

-1.37, 2.58

0.549

time_point

1st

—

—

—

2nd

-0.875

0.792

-2.43, 0.677

0.273

group * time_point

treatment * 2nd

1.66

1.140

-0.572, 3.90

0.150

Pseudo R square

0.012

satisfaction

(Intercept)

20.0

0.862

18.3, 21.7

group

control

—

—

—

treatment

1.20

1.228

-1.20, 3.61

0.329

time_point

1st

—

—

—

2nd

0.548

1.047

-1.50, 2.60

0.602

group * time_point

treatment * 2nd

0.580

1.508

-2.38, 3.54

0.702

Pseudo R square

0.012

mhc_emotional

(Intercept)

10.7

0.450

9.81, 11.6

group

control

—

—

—

treatment

0.513

0.641

-0.744, 1.77

0.425

time_point

1st

—

—

—

2nd

0.275

0.493

-0.690, 1.24

0.578

group * time_point

treatment * 2nd

-0.094

0.710

-1.48, 1.30

0.895

Pseudo R square

0.005

mhc_social

(Intercept)

14.7

0.683

13.4, 16.1

group

control

—

—

—

treatment

0.674

0.972

-1.23, 2.58

0.489

time_point

1st

—

—

—

2nd

0.644

0.849

-1.02, 2.31

0.451

group * time_point

treatment * 2nd

-0.406

1.222

-2.80, 1.99

0.741

Pseudo R square

0.004

mhc_psychological

(Intercept)

21.8

0.794

20.2, 23.4

group

control

—

—

—

treatment

0.284

1.131

-1.93, 2.50

0.802

time_point

1st

—

—

—

2nd

0.438

0.969

-1.46, 2.34

0.653

group * time_point

treatment * 2nd

0.276

1.396

-2.46, 3.01

0.844

Pseudo R square

0.002

resilisnce

(Intercept)

16.3

0.549

15.2, 17.3

group

control

—

—

—

treatment

0.877

0.782

-0.657, 2.41

0.264

time_point

1st

—

—

—

2nd

0.108

0.695

-1.25, 1.47

0.877

group * time_point

treatment * 2nd

1.49

1.000

-0.472, 3.45

0.142

Pseudo R square

0.030

social_provision

(Intercept)

13.1

0.343

12.4, 13.8

group

control

—

—

—

treatment

0.916

0.489

-0.042, 1.87

0.063

time_point

1st

—

—

—

2nd

-0.524

0.457

-1.42, 0.372

0.255

group * time_point

treatment * 2nd

0.697

0.658

-0.593, 1.99

0.293

Pseudo R square

0.039

els_value_living

(Intercept)

16.6

0.379

15.8, 17.3

group

control

—

—

—

treatment

0.756

0.540

-0.301, 1.81

0.163

time_point

1st

—

—

—

2nd

0.244

0.472

-0.680, 1.17

0.607

group * time_point

treatment * 2nd

0.283

0.679

-1.05, 1.61

0.679

Pseudo R square

0.020

els_life_fulfill

(Intercept)

12.4

0.403

11.6, 13.2

group

control

—

—

—

treatment

0.779

0.573

-0.345, 1.90

0.176

time_point

1st

—

—

—

2nd

0.472

0.402

-0.315, 1.26

0.245

group * time_point

treatment * 2nd

-0.125

0.579

-1.26, 1.01

0.830

Pseudo R square

0.015

els

(Intercept)

29.0

0.713

27.6, 30.4

group

control

—

—

—

treatment

1.54

1.016

-0.457, 3.53

0.133

time_point

1st

—

—

—

2nd

0.700

0.729

-0.729, 2.13

0.341

group * time_point

treatment * 2nd

0.159

1.051

-1.90, 2.22

0.880

Pseudo R square

0.020

social_connect

(Intercept)

26.7

1.141

24.5, 29.0

group

control

—

—

—

treatment

-0.544

1.625

-3.73, 2.64

0.738

time_point

1st

—

—

—

2nd

1.17

1.192

-1.17, 3.51

0.330

group * time_point

treatment * 2nd

-3.69

1.717

-7.06, -0.329

0.035

Pseudo R square

0.015

shs_agency

(Intercept)

14.0

0.612

12.8, 15.2

group

control

—

—

—

treatment

0.796

0.872

-0.912, 2.50

0.362

time_point

1st

—

—

—

2nd

0.087

0.665

-1.22, 1.39

0.897

group * time_point

treatment * 2nd

0.789

0.957

-1.09, 2.67

0.413

Pseudo R square

0.012

shs_pathway

(Intercept)

15.7

0.477

14.8, 16.7

group

control

—

—

—

treatment

0.645

0.679

-0.686, 1.98

0.344

time_point

1st

—

—

—

2nd

0.233

0.516

-0.778, 1.24

0.653

group * time_point

treatment * 2nd

-0.071

0.743

-1.53, 1.38

0.924

Pseudo R square

0.007

shs

(Intercept)

29.7

1.040

27.7, 31.8

group

control

—

—

—

treatment

1.44

1.481

-1.46, 4.34

0.332

time_point

1st

—

—

—

2nd

0.324

1.081

-1.79, 2.44

0.766

group * time_point

treatment * 2nd

0.694

1.556

-2.36, 3.74

0.657

Pseudo R square

0.010

esteem

(Intercept)

12.6

0.185

12.3, 13.0

group

control

—

—

—

treatment

-0.068

0.263

-0.584, 0.448

0.796

time_point

1st

—

—

—

2nd

0.024

0.294

-0.552, 0.601

0.934

group * time_point

treatment * 2nd

0.149

0.423

-0.681, 0.978

0.727

Pseudo R square

0.001

mlq_search

(Intercept)

14.7

0.413

13.9, 15.5

group

control

—

—

—

treatment

0.267

0.588

-0.885, 1.42

0.651

time_point

1st

—

—

—

2nd

0.199

0.583

-0.944, 1.34

0.733

group * time_point

treatment * 2nd

-0.243

0.839

-1.89, 1.40

0.773

Pseudo R square

0.001

mlq_presence

(Intercept)

13.4

0.497

12.4, 14.4

group

control

—

—

—

treatment

0.272

0.708

-1.11, 1.66

0.701

time_point

1st

—

—

—

2nd

0.210

0.618

-1.00, 1.42

0.735

group * time_point

treatment * 2nd

0.082

0.890

-1.66, 1.83

0.927

Pseudo R square

0.002

mlq

(Intercept)

28.1

0.823

26.5, 29.7

group

control

—

—

—

treatment

0.539

1.173

-1.76, 2.84

0.647

time_point

1st

—

—

—

2nd

0.422

1.064

-1.66, 2.51

0.693

group * time_point

treatment * 2nd

-0.152

1.532

-3.15, 2.85

0.921

Pseudo R square

0.002

empower

(Intercept)

19.0

0.508

18.0, 20.0

group

control

—

—

—

treatment

0.637

0.723

-0.781, 2.05

0.380

time_point

1st

—

—

—

2nd

0.245

0.539

-0.811, 1.30

0.651

group * time_point

treatment * 2nd

-0.513

0.776

-2.03, 1.01

0.511

Pseudo R square

0.004

ismi_resistance

(Intercept)

14.5

0.296

13.9, 15.1

group

control

—

—

—

treatment

0.144

0.422

-0.683, 0.972

0.733

time_point

1st

—

—

—

2nd

-0.061

0.438

-0.919, 0.798

0.890

group * time_point

treatment * 2nd

0.538

0.630

-0.697, 1.77

0.395

Pseudo R square

0.007

ismi_discrimation

(Intercept)

12.0

0.375

11.2, 12.7

group

control

—

—

—

treatment

-0.740

0.534

-1.79, 0.306

0.168

time_point

1st

—

—

—

2nd

-0.304

0.449

-1.18, 0.576

0.501

group * time_point

treatment * 2nd

0.226

0.647

-1.04, 1.49

0.728

Pseudo R square

0.012

sss_affective

(Intercept)

10.0

0.415

9.21, 10.8

group

control

—

—

—

treatment

-0.217

0.592

-1.38, 0.943

0.715

time_point

1st

—

—

—

2nd

0.139

0.485

-0.811, 1.09

0.775

group * time_point

treatment * 2nd

-1.19

0.698

-2.56, 0.177

0.093

Pseudo R square

0.015

sss_behavior

(Intercept)

9.89

0.441

9.02, 10.8

group

control

—

—

—

treatment

-0.453

0.628

-1.68, 0.779

0.472

time_point

1st

—

—

—

2nd

-0.013

0.524

-1.04, 1.01

0.981

group * time_point

treatment * 2nd

-0.727

0.754

-2.21, 0.752

0.339

Pseudo R square

0.011

sss_cognitive

(Intercept)

8.24

0.440

7.38, 9.10

group

control

—

—

—

treatment

-0.095

0.626

-1.32, 1.13

0.880

time_point

1st

—

—

—

2nd

0.680

0.513

-0.325, 1.68

0.189

group * time_point

treatment * 2nd

-1.37

0.738

-2.82, 0.073

0.067

Pseudo R square

0.011

sss

(Intercept)

28.2

1.202

25.8, 30.5

group

control

—

—

—

treatment

-0.764

1.712

-4.12, 2.59

0.656

time_point

1st

—

—

—

2nd

0.733

1.292

-1.80, 3.26

0.573

group * time_point

treatment * 2nd

-3.11

1.861

-6.76, 0.536

0.099

Pseudo R square

0.012

1SE = Standard Error, CI = Confidence Interval

Text

recovery_stage_a

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict recovery_stage_a with group and time_point (formula: recovery_stage_a ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.34) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 3.27 (95% CI [3.00, 3.54], t(188) = 23.71, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.14, 95% CI [-0.52, 0.25], t(188) = -0.70, p = 0.485; Std. beta = -0.12, 95% CI [-0.45, 0.21])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -3.02e-04, 95% CI [-0.45, 0.45], t(188) = -1.33e-03, p = 0.999; Std. beta = -2.59e-04, 95% CI [-0.38, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.49, 95% CI [-0.15, 1.13], t(188) = 1.50, p = 0.133; Std. beta = 0.42, 95% CI [-0.13, 0.97])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

recovery_stage_b

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict recovery_stage_b with group and time_point (formula: recovery_stage_b ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.43) and the part related to the fixed effects alone (marginal R2) is of 7.96e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 17.90 (95% CI [17.23, 18.57], t(188) = 52.61, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-0.81, 1.09], t(188) = 0.29, p = 0.769; Std. beta = 0.05, 95% CI [-0.28, 0.38])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.38, 95% CI [-1.41, 0.66], t(188) = -0.71, p = 0.475; Std. beta = -0.13, 95% CI [-0.49, 0.23])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.80, 95% CI [-0.69, 2.29], t(188) = 1.06, p = 0.291; Std. beta = 0.28, 95% CI [-0.24, 0.80])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_confidence

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_confidence with group and time_point (formula: ras_confidence ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 29.83 (95% CI [28.62, 31.04], t(188) = 48.22, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.40, 95% CI [-1.33, 2.13], t(188) = 0.45, p = 0.649; Std. beta = 0.08, 95% CI [-0.26, 0.41])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.69, 95% CI [-0.75, 2.14], t(188) = 0.94, p = 0.345; Std. beta = 0.13, 95% CI [-0.14, 0.41])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.12, 95% CI [-0.95, 3.20], t(188) = 1.06, p = 0.290; Std. beta = 0.22, 95% CI [-0.18, 0.62])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_willingness

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_willingness with group and time_point (formula: ras_willingness ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.66 (95% CI [11.17, 12.15], t(188) = 46.84, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.43, 0.96], t(188) = 0.75, p = 0.454; Std. beta = 0.13, 95% CI [-0.21, 0.46])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.48, 95% CI [-1.07, 0.11], t(188) = -1.60, p = 0.109; Std. beta = -0.23, 95% CI [-0.51, 0.05])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.69, 95% CI [-0.15, 1.54], t(188) = 1.60, p = 0.109; Std. beta = 0.33, 95% CI [-0.07, 0.74])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_goal

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_goal with group and time_point (formula: ras_goal ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.64) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 17.14 (95% CI [16.40, 17.88], t(188) = 45.64, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.50, 95% CI [-0.55, 1.55], t(188) = 0.93, p = 0.353; Std. beta = 0.16, 95% CI [-0.17, 0.49])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.46, 95% CI [-1.41, 0.49], t(188) = -0.94, p = 0.345; Std. beta = -0.14, 95% CI [-0.44, 0.16])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 1.57, 95% CI [0.19, 2.94], t(188) = 2.24, p = 0.025; Std. beta = 0.49, 95% CI [0.06, 0.93])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_reliance

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_reliance with group and time_point (formula: ras_reliance ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.99 (95% CI [12.30, 13.67], t(188) = 37.35, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.43, 95% CI [-0.54, 1.41], t(188) = 0.88, p = 0.380; Std. beta = 0.15, 95% CI [-0.18, 0.47])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.34, 95% CI [-0.44, 1.11], t(188) = 0.84, p = 0.398; Std. beta = 0.11, 95% CI [-0.15, 0.37])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.04, 95% CI [-0.08, 2.17], t(188) = 1.83, p = 0.068; Std. beta = 0.35, 95% CI [-0.03, 0.73])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ras_domination

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ras_domination with group and time_point (formula: ras_domination ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.50) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.17 (95% CI [9.62, 10.72], t(188) = 36.11, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.50, 95% CI [-1.29, 0.28], t(188) = -1.25, p = 0.210; Std. beta = -0.21, 95% CI [-0.55, 0.12])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.31, 95% CI [-1.13, 0.50], t(188) = -0.76, p = 0.450; Std. beta = -0.13, 95% CI [-0.48, 0.21])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and positive (beta = 1.42, 95% CI [0.25, 2.60], t(188) = 2.37, p = 0.018; Std. beta = 0.60, 95% CI [0.11, 1.10])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

symptom

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict symptom with group and time_point (formula: symptom ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.81) and the part related to the fixed effects alone (marginal R2) is of 3.09e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 29.93 (95% CI [27.74, 32.12], t(187) = 26.79, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.01, 95% CI [-3.12, 3.14], t(187) = 7.26e-03, p = 0.994; Std. beta = 1.23e-03, 95% CI [-0.33, 0.33])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.37, 95% CI [-2.47, 1.74], t(187) = -0.34, p = 0.732; Std. beta = -0.04, 95% CI [-0.26, 0.18])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.18, 95% CI [-4.21, 1.85], t(187) = -0.77, p = 0.444; Std. beta = -0.13, 95% CI [-0.45, 0.20])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

slof_work

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict slof_work with group and time_point (formula: slof_work ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 3.85e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 22.85 (95% CI [21.74, 23.95], t(188) = 40.46, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.67, 95% CI [-2.25, 0.91], t(188) = -0.83, p = 0.404; Std. beta = -0.14, 95% CI [-0.47, 0.19])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.34, 95% CI [-1.59, 0.90], t(188) = -0.54, p = 0.589; Std. beta = -0.07, 95% CI [-0.34, 0.19])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.46, 95% CI [-1.34, 2.26], t(188) = 0.50, p = 0.615; Std. beta = 0.10, 95% CI [-0.28, 0.48])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

slof_relationship

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict slof_relationship with group and time_point (formula: slof_relationship ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.73) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 24.90 (95% CI [23.51, 26.29], t(188) = 35.17, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.61, 95% CI [-1.37, 2.58], t(188) = 0.60, p = 0.548; Std. beta = 0.10, 95% CI [-0.23, 0.44])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.88, 95% CI [-2.43, 0.68], t(188) = -1.11, p = 0.269; Std. beta = -0.15, 95% CI [-0.41, 0.11])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.66, 95% CI [-0.57, 3.90], t(188) = 1.46, p = 0.145; Std. beta = 0.28, 95% CI [-0.10, 0.66])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

satisfaction

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict satisfaction with group and time_point (formula: satisfaction ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.68) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 19.99 (95% CI [18.30, 21.68], t(188) = 23.18, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.20, 95% CI [-1.20, 3.61], t(188) = 0.98, p = 0.327; Std. beta = 0.17, 95% CI [-0.17, 0.50])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.55, 95% CI [-1.50, 2.60], t(188) = 0.52, p = 0.600; Std. beta = 0.08, 95% CI [-0.21, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.58, 95% CI [-2.38, 3.54], t(188) = 0.38, p = 0.700; Std. beta = 0.08, 95% CI [-0.33, 0.49])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_emotional

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_emotional with group and time_point (formula: mhc_emotional ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.74) and the part related to the fixed effects alone (marginal R2) is of 4.85e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.69 (95% CI [9.81, 11.57], t(188) = 23.75, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.51, 95% CI [-0.74, 1.77], t(188) = 0.80, p = 0.424; Std. beta = 0.14, 95% CI [-0.20, 0.47])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.28, 95% CI [-0.69, 1.24], t(188) = 0.56, p = 0.576; Std. beta = 0.07, 95% CI [-0.18, 0.33])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.09, 95% CI [-1.48, 1.30], t(188) = -0.13, p = 0.895; Std. beta = -0.02, 95% CI [-0.39, 0.34])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_social

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_social with group and time_point (formula: mhc_social ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 3.81e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.75 (95% CI [13.41, 16.08], t(188) = 21.61, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.67, 95% CI [-1.23, 2.58], t(188) = 0.69, p = 0.488; Std. beta = 0.12, 95% CI [-0.22, 0.45])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.64, 95% CI [-1.02, 2.31], t(188) = 0.76, p = 0.448; Std. beta = 0.11, 95% CI [-0.18, 0.41])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.41, 95% CI [-2.80, 1.99], t(188) = -0.33, p = 0.740; Std. beta = -0.07, 95% CI [-0.49, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mhc_psychological

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mhc_psychological with group and time_point (formula: mhc_psychological ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 2.26e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 21.80 (95% CI [20.25, 23.36], t(188) = 27.46, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.28, 95% CI [-1.93, 2.50], t(188) = 0.25, p = 0.802; Std. beta = 0.04, 95% CI [-0.29, 0.38])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.44, 95% CI [-1.46, 2.34], t(188) = 0.45, p = 0.652; Std. beta = 0.07, 95% CI [-0.22, 0.35])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.28, 95% CI [-2.46, 3.01], t(188) = 0.20, p = 0.844; Std. beta = 0.04, 95% CI [-0.37, 0.45])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

resilisnce

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict resilisnce with group and time_point (formula: resilisnce ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 0.03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.25 (95% CI [15.18, 17.33], t(188) = 29.59, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.88, 95% CI [-0.66, 2.41], t(188) = 1.12, p = 0.262; Std. beta = 0.19, 95% CI [-0.14, 0.52])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.11, 95% CI [-1.25, 1.47], t(188) = 0.16, p = 0.876; Std. beta = 0.02, 95% CI [-0.27, 0.32])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 1.49, 95% CI [-0.47, 3.45], t(188) = 1.49, p = 0.137; Std. beta = 0.32, 95% CI [-0.10, 0.75])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

social_provision

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict social_provision with group and time_point (formula: social_provision ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.62) and the part related to the fixed effects alone (marginal R2) is of 0.04. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.11 (95% CI [12.44, 13.79], t(188) = 38.22, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.92, 95% CI [-0.04, 1.87], t(188) = 1.87, p = 0.061; Std. beta = 0.31, 95% CI [-0.01, 0.64])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.52, 95% CI [-1.42, 0.37], t(188) = -1.15, p = 0.252; Std. beta = -0.18, 95% CI [-0.48, 0.13])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.70, 95% CI [-0.59, 1.99], t(188) = 1.06, p = 0.290; Std. beta = 0.24, 95% CI [-0.20, 0.67])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els_value_living

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els_value_living with group and time_point (formula: els_value_living ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.67) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 16.59 (95% CI [15.85, 17.33], t(188) = 43.79, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.76, 95% CI [-0.30, 1.81], t(188) = 1.40, p = 0.161; Std. beta = 0.24, 95% CI [-0.09, 0.57])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.24, 95% CI [-0.68, 1.17], t(188) = 0.52, p = 0.605; Std. beta = 0.08, 95% CI [-0.21, 0.37])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.28, 95% CI [-1.05, 1.61], t(188) = 0.42, p = 0.677; Std. beta = 0.09, 95% CI [-0.33, 0.50])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els_life_fulfill

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els_life_fulfill with group and time_point (formula: els_life_fulfill ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.79) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.37 (95% CI [11.58, 13.16], t(188) = 30.72, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.78, 95% CI [-0.35, 1.90], t(188) = 1.36, p = 0.174; Std. beta = 0.23, 95% CI [-0.10, 0.57])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.47, 95% CI [-0.32, 1.26], t(188) = 1.18, p = 0.240; Std. beta = 0.14, 95% CI [-0.09, 0.38])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.12, 95% CI [-1.26, 1.01], t(188) = -0.22, p = 0.829; Std. beta = -0.04, 95% CI [-0.38, 0.30])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

els

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict els with group and time_point (formula: els ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.78) and the part related to the fixed effects alone (marginal R2) is of 0.02. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.96 (95% CI [27.56, 30.36], t(188) = 40.59, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.54, 95% CI [-0.46, 3.53], t(188) = 1.51, p = 0.131; Std. beta = 0.26, 95% CI [-0.08, 0.59])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.70, 95% CI [-0.73, 2.13], t(188) = 0.96, p = 0.337; Std. beta = 0.12, 95% CI [-0.12, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.16, 95% CI [-1.90, 2.22], t(188) = 0.15, p = 0.880; Std. beta = 0.03, 95% CI [-0.32, 0.37])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

social_connect

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict social_connect with group and time_point (formula: social_connect ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 26.73 (95% CI [24.50, 28.97], t(188) = 23.44, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.54, 95% CI [-3.73, 2.64], t(188) = -0.33, p = 0.738; Std. beta = -0.06, 95% CI [-0.39, 0.27])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 1.17, 95% CI [-1.17, 3.51], t(188) = 0.98, p = 0.326; Std. beta = 0.12, 95% CI [-0.12, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically significant and negative (beta = -3.69, 95% CI [-7.06, -0.33], t(188) = -2.15, p = 0.031; Std. beta = -0.38, 95% CI [-0.73, -0.03])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs_agency

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs_agency with group and time_point (formula: shs_agency ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.97 (95% CI [12.77, 15.17], t(188) = 22.84, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.80, 95% CI [-0.91, 2.50], t(188) = 0.91, p = 0.361; Std. beta = 0.16, 95% CI [-0.18, 0.49])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.09, 95% CI [-1.22, 1.39], t(188) = 0.13, p = 0.896; Std. beta = 0.02, 95% CI [-0.24, 0.27])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.79, 95% CI [-1.09, 2.67], t(188) = 0.82, p = 0.410; Std. beta = 0.16, 95% CI [-0.21, 0.53])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs_pathway

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs_pathway with group and time_point (formula: shs_pathway ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.75) and the part related to the fixed effects alone (marginal R2) is of 6.51e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 15.75 (95% CI [14.81, 16.68], t(188) = 33.04, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.64, 95% CI [-0.69, 1.98], t(188) = 0.95, p = 0.342; Std. beta = 0.16, 95% CI [-0.17, 0.50])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.23, 95% CI [-0.78, 1.24], t(188) = 0.45, p = 0.651; Std. beta = 0.06, 95% CI [-0.20, 0.31])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-1.53, 1.38], t(188) = -0.10, p = 0.923; Std. beta = -0.02, 95% CI [-0.39, 0.35])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

shs

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict shs with group and time_point (formula: shs ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.77) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 29.72 (95% CI [27.68, 31.76], t(188) = 28.58, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 1.44, 95% CI [-1.46, 4.34], t(188) = 0.97, p = 0.331; Std. beta = 0.17, 95% CI [-0.17, 0.50])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.32, 95% CI [-1.79, 2.44], t(188) = 0.30, p = 0.765; Std. beta = 0.04, 95% CI [-0.21, 0.28])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.69, 95% CI [-2.36, 3.74], t(188) = 0.45, p = 0.656; Std. beta = 0.08, 95% CI [-0.27, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

esteem

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict esteem with group and time_point (formula: esteem ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.39) and the part related to the fixed effects alone (marginal R2) is of 1.31e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 12.65 (95% CI [12.29, 13.01], t(188) = 68.47, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.07, 95% CI [-0.58, 0.45], t(188) = -0.26, p = 0.796; Std. beta = -0.04, 95% CI [-0.38, 0.29])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.02, 95% CI [-0.55, 0.60], t(188) = 0.08, p = 0.934; Std. beta = 0.02, 95% CI [-0.36, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.15, 95% CI [-0.68, 0.98], t(188) = 0.35, p = 0.725; Std. beta = 0.10, 95% CI [-0.45, 0.64])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq_search

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq_search with group and time_point (formula: mlq_search ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.54) and the part related to the fixed effects alone (marginal R2) is of 1.17e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.70 (95% CI [13.90, 15.51], t(188) = 35.63, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-0.89, 1.42], t(188) = 0.45, p = 0.650; Std. beta = 0.08, 95% CI [-0.26, 0.41])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.20, 95% CI [-0.94, 1.34], t(188) = 0.34, p = 0.732; Std. beta = 0.06, 95% CI [-0.27, 0.39])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.24, 95% CI [-1.89, 1.40], t(188) = -0.29, p = 0.772; Std. beta = -0.07, 95% CI [-0.55, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq_presence

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq_presence with group and time_point (formula: mlq_presence ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.66) and the part related to the fixed effects alone (marginal R2) is of 1.96e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 13.38 (95% CI [12.41, 14.35], t(188) = 26.94, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.27, 95% CI [-1.11, 1.66], t(188) = 0.38, p = 0.701; Std. beta = 0.07, 95% CI [-0.27, 0.40])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.21, 95% CI [-1.00, 1.42], t(188) = 0.34, p = 0.734; Std. beta = 0.05, 95% CI [-0.24, 0.34])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.08, 95% CI [-1.66, 1.83], t(188) = 0.09, p = 0.927; Std. beta = 0.02, 95% CI [-0.40, 0.44])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

mlq

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict mlq with group and time_point (formula: mlq ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.63) and the part related to the fixed effects alone (marginal R2) is of 1.80e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.08 (95% CI [26.47, 29.70], t(188) = 34.11, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.54, 95% CI [-1.76, 2.84], t(188) = 0.46, p = 0.646; Std. beta = 0.08, 95% CI [-0.26, 0.41])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.42, 95% CI [-1.66, 2.51], t(188) = 0.40, p = 0.692; Std. beta = 0.06, 95% CI [-0.24, 0.36])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.15, 95% CI [-3.15, 2.85], t(188) = -0.10, p = 0.921; Std. beta = -0.02, 95% CI [-0.46, 0.41])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

empower

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict empower with group and time_point (formula: empower ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 4.06e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 18.97 (95% CI [17.98, 19.97], t(188) = 37.36, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.64, 95% CI [-0.78, 2.05], t(188) = 0.88, p = 0.379; Std. beta = 0.15, 95% CI [-0.18, 0.48])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.25, 95% CI [-0.81, 1.30], t(188) = 0.46, p = 0.649; Std. beta = 0.06, 95% CI [-0.19, 0.31])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.51, 95% CI [-2.03, 1.01], t(188) = -0.66, p = 0.509; Std. beta = -0.12, 95% CI [-0.48, 0.24])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ismi_resistance

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ismi_resistance with group and time_point (formula: ismi_resistance ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.49) and the part related to the fixed effects alone (marginal R2) is of 7.03e-03. The model’s intercept, corresponding to group = control and time_point = 1st, is at 14.48 (95% CI [13.90, 15.06], t(188) = 48.85, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and positive (beta = 0.14, 95% CI [-0.68, 0.97], t(188) = 0.34, p = 0.732; Std. beta = 0.06, 95% CI [-0.27, 0.39])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.06, 95% CI [-0.92, 0.80], t(188) = -0.14, p = 0.890; Std. beta = -0.02, 95% CI [-0.37, 0.32])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.54, 95% CI [-0.70, 1.77], t(188) = 0.85, p = 0.393; Std. beta = 0.22, 95% CI [-0.28, 0.71])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

ismi_discrimation

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict ismi_discrimation with group and time_point (formula: ismi_discrimation ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.69) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 11.96 (95% CI [11.22, 12.69], t(188) = 31.90, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.74, 95% CI [-1.79, 0.31], t(188) = -1.39, p = 0.166; Std. beta = -0.23, 95% CI [-0.56, 0.10])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.30, 95% CI [-1.18, 0.58], t(188) = -0.68, p = 0.499; Std. beta = -0.10, 95% CI [-0.37, 0.18])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and positive (beta = 0.23, 95% CI [-1.04, 1.49], t(188) = 0.35, p = 0.727; Std. beta = 0.07, 95% CI [-0.33, 0.47])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_affective

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_affective with group and time_point (formula: sss_affective ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 10.03 (95% CI [9.21, 10.84], t(188) = 24.15, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.22, 95% CI [-1.38, 0.94], t(188) = -0.37, p = 0.714; Std. beta = -0.06, 95% CI [-0.39, 0.26])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.14, 95% CI [-0.81, 1.09], t(188) = 0.29, p = 0.774; Std. beta = 0.04, 95% CI [-0.23, 0.31])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.19, 95% CI [-2.56, 0.18], t(188) = -1.71, p = 0.088; Std. beta = -0.33, 95% CI [-0.72, 0.05])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_behavior

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_behavior with group and time_point (formula: sss_behavior ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.70) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 9.89 (95% CI [9.02, 10.75], t(188) = 22.42, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.45, 95% CI [-1.68, 0.78], t(188) = -0.72, p = 0.471; Std. beta = -0.12, 95% CI [-0.45, 0.21])
  • The effect of time point [2nd] is statistically non-significant and negative (beta = -0.01, 95% CI [-1.04, 1.01], t(188) = -0.02, p = 0.981; Std. beta = -3.37e-03, 95% CI [-0.28, 0.27])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -0.73, 95% CI [-2.21, 0.75], t(188) = -0.96, p = 0.335; Std. beta = -0.19, 95% CI [-0.59, 0.20])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss_cognitive

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss_cognitive with group and time_point (formula: sss_cognitive ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.71) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 8.24 (95% CI [7.38, 9.10], t(188) = 18.74, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.09, 95% CI [-1.32, 1.13], t(188) = -0.15, p = 0.880; Std. beta = -0.03, 95% CI [-0.35, 0.30])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.68, 95% CI [-0.33, 1.68], t(188) = 1.33, p = 0.185; Std. beta = 0.18, 95% CI [-0.09, 0.45])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -1.37, 95% CI [-2.82, 0.07], t(188) = -1.86, p = 0.063; Std. beta = -0.37, 95% CI [-0.75, 0.02])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

sss

We fitted a linear mixed model (estimated using REML and nloptwrap optimizer) to predict sss with group and time_point (formula: sss ~ 1 + group + time_point + group * time_point). The model included mobile as random effect (formula: ~1 | mobile). The model’s total explanatory power is substantial (conditional R2 = 0.76) and the part related to the fixed effects alone (marginal R2) is of 0.01. The model’s intercept, corresponding to group = control and time_point = 1st, is at 28.15 (95% CI [25.80, 30.51], t(188) = 23.42, p < .001). Within this model:

  • The effect of group [treatment] is statistically non-significant and negative (beta = -0.76, 95% CI [-4.12, 2.59], t(188) = -0.45, p = 0.656; Std. beta = -0.07, 95% CI [-0.40, 0.25])
  • The effect of time point [2nd] is statistically non-significant and positive (beta = 0.73, 95% CI [-1.80, 3.26], t(188) = 0.57, p = 0.571; Std. beta = 0.07, 95% CI [-0.17, 0.32])
  • The interaction effect of time point [2nd] on group [treatment] is statistically non-significant and negative (beta = -3.11, 95% CI [-6.76, 0.54], t(188) = -1.67, p = 0.095; Std. beta = -0.30, 95% CI [-0.65, 0.05])

Standardized parameters were obtained by fitting the model on a standardized version of the dataset. 95% Confidence Intervals (CIs) and p-values were computed using a Wald normal distribution approximation.

Likelihood ratio tests

outcome

model

npar

AIC

BIC

logLik

deviance

Chisq

Df

p

recovery_stage_a

null

3

608.957

618.760

-301.478

602.957

recovery_stage_a

random

6

610.555

630.162

-299.278

598.555

4.402

3

0.221

recovery_stage_b

null

3

952.069

961.872

-473.034

946.069

recovery_stage_b

random

6

956.388

975.995

-472.194

944.388

1.681

3

0.641

ras_confidence

null

3

1,164.852

1,174.655

-579.426

1,158.852

ras_confidence

random

6

1,163.813

1,183.420

-575.907

1,151.813

7.038

3

0.071

ras_willingness

null

3

810.251

820.054

-402.125

804.251

ras_willingness

random

6

811.758

831.365

-399.879

799.758

4.493

3

0.213

ras_goal

null

3

980.771

990.575

-487.386

974.771

ras_goal

random

6

978.559

998.166

-483.280

966.559

8.212

3

0.042

ras_reliance

null

3

943.532

953.336

-468.766

937.532

ras_reliance

random

6

936.308

955.915

-462.154

924.308

13.224

3

0.004

ras_domination

null

3

879.953

889.757

-436.977

873.953

ras_domination

random

6

878.854

898.462

-433.427

866.854

7.099

3

0.069

symptom

null

3

1,360.446

1,370.234

-677.223

1,354.446

symptom

random

6

1,364.342

1,383.918

-676.171

1,352.342

2.104

3

0.551

slof_work

null

3

1,118.093

1,127.896

-556.046

1,112.093

slof_work

random

6

1,123.215

1,142.822

-555.607

1,111.215

0.878

3

0.831

slof_relationship

null

3

1,207.212

1,217.016

-600.606

1,201.212

slof_relationship

random

6

1,210.078

1,229.685

-599.039

1,198.078

3.134

3

0.371

satisfaction

null

3

1,291.330

1,301.134

-642.665

1,285.330

satisfaction

random

6

1,294.703

1,314.310

-641.352

1,282.703

2.627

3

0.453

mhc_emotional

null

3

1,027.262

1,037.065

-510.631

1,021.262

mhc_emotional

random

6

1,032.186

1,051.793

-510.093

1,020.186

1.076

3

0.783

mhc_social

null

3

1,201.448

1,211.252

-597.724

1,195.448

mhc_social

random

6

1,206.388

1,225.995

-597.194

1,194.388

1.061

3

0.787

mhc_psychological

null

3

1,258.102

1,267.906

-626.051

1,252.102

mhc_psychological

random

6

1,263.278

1,282.885

-625.639

1,251.278

0.825

3

0.844

resilisnce

null

3

1,125.083

1,134.887

-559.542

1,119.083

resilisnce

random

6

1,123.737

1,143.344

-555.868

1,111.737

7.347

3

0.062

social_provision

null

3

946.852

956.655

-470.426

940.852

social_provision

random

6

946.126

965.733

-467.063

934.126

6.726

3

0.081

els_value_living

null

3

975.986

985.790

-484.993

969.986

els_value_living

random

6

978.067

997.675

-483.034

966.067

3.919

3

0.270

els_life_fulfill

null

3

977.374

987.177

-485.687

971.374

els_life_fulfill

random

6

979.461

999.068

-483.731

967.461

3.913

3

0.271

els

null

3

1,202.758

1,212.561

-598.379

1,196.758

els

random

6

1,204.028

1,223.636

-596.014

1,192.028

4.729

3

0.193

social_connect

null

3

1,388.105

1,397.909

-691.053

1,382.105

social_connect

random

6

1,388.307

1,407.914

-688.154

1,376.307

5.798

3

0.122

shs_agency

null

3

1,147.511

1,157.315

-570.756

1,141.511

shs_agency

random

6

1,150.562

1,170.169

-569.281

1,138.562

2.950

3

0.399

shs_pathway

null

3

1,048.476

1,058.279

-521.238

1,042.476

shs_pathway

random

6

1,053.267

1,072.874

-520.634

1,041.267

1.208

3

0.751

shs

null

3

1,348.000

1,357.804

-671.000

1,342.000

shs

random

6

1,351.863

1,371.470

-669.932

1,339.863

2.137

3

0.544

esteem

null

3

715.814

725.617

-354.907

709.814

esteem

random

6

721.452

741.059

-354.726

709.452

0.362

3

0.948

mlq_search

null

3

1,017.468

1,027.272

-505.734

1,011.468

mlq_search

random

6

1,023.196

1,042.803

-505.598

1,011.196

0.272

3

0.965

mlq_presence

null

3

1,077.588

1,087.392

-535.794

1,071.588

mlq_presence

random

6

1,083.073

1,102.680

-535.536

1,071.073

0.515

3

0.915

mlq

null

3

1,277.293

1,287.096

-635.646

1,271.293

mlq

random

6

1,282.865

1,302.473

-635.433

1,270.865

0.427

3

0.935

empower

null

3

1,070.845

1,080.649

-532.422

1,064.845

empower

random

6

1,075.823

1,095.430

-531.911

1,063.823

1.022

3

0.796

ismi_resistance

null

3

894.317

904.120

-444.158

888.317

ismi_resistance

random

6

898.710

918.318

-443.355

886.710

1.606

3

0.658

ismi_discrimation

null

3

966.505

976.309

-480.253

960.505

ismi_discrimation

random

6

970.205

989.812

-479.103

958.205

2.300

3

0.512

sss_affective

null

3

1,006.558

1,016.362

-500.279

1,000.558

sss_affective

random

6

1,007.390

1,026.997

-497.695

995.390

5.168

3

0.160

sss_behavior

null

3

1,029.342

1,039.146

-511.671

1,023.342

sss_behavior

random

6

1,032.472

1,052.079

-510.236

1,020.472

2.870

3

0.412

sss_cognitive

null

3

1,027.292

1,037.096

-510.646

1,021.292

sss_cognitive

random

6

1,029.374

1,048.981

-508.687

1,017.374

3.918

3

0.270

sss

null

3

1,409.746

1,419.550

-701.873

1,403.746

sss

random

6

1,411.514

1,431.121

-699.757

1,399.514

4.232

3

0.237

Post hoc analysis

Table

outcome

time

control

treatment

between

n

estimate

within es

n

estimate

within es

p

es

recovery_stage_a

1st

71

3.27 ± 1.16

69

3.13 ± 1.16

0.486

0.144

recovery_stage_a

2nd

28

3.27 ± 1.13

0.000

26

3.62 ± 1.13

-0.514

0.253

-0.371

recovery_stage_b

1st

71

17.90 ± 2.87

69

18.04 ± 2.87

0.770

-0.065

recovery_stage_b

2nd

28

17.52 ± 2.73

0.174

26

18.47 ± 2.72

-0.196

0.205

-0.435

ras_confidence

1st

71

29.83 ± 5.21

69

30.23 ± 5.21

0.650

-0.139

ras_confidence

2nd

28

30.53 ± 4.41

-0.240

26

32.05 ± 4.38

-0.629

0.205

-0.527

ras_willingness

1st

71

11.66 ± 2.10

69

11.93 ± 2.10

0.455

-0.226

ras_willingness

2nd

28

11.18 ± 1.78

0.408

26

12.14 ± 1.77

-0.179

0.050

-0.812

ras_goal

1st

71

17.14 ± 3.16

69

17.64 ± 3.16

0.354

-0.257

ras_goal

2nd

28

16.68 ± 2.78

0.238

26

18.75 ± 2.76

-0.573

0.007

-1.067

ras_reliance

1st

71

12.99 ± 2.93

69

13.42 ± 2.93

0.382

-0.280

ras_reliance

2nd

28

13.32 ± 2.44

-0.216

26

14.80 ± 2.42

-0.888

0.027

-0.951

ras_domination

1st

71

10.17 ± 2.37

69

9.67 ± 2.37

0.212

0.297

ras_domination

2nd

28

9.85 ± 2.21

0.186

26

10.77 ± 2.20

-0.655

0.128

-0.543

symptom

1st

71

29.93 ± 9.41

68

29.94 ± 9.41

0.994

-0.003

symptom

2nd

28

29.56 ± 7.34

0.089

26

28.39 ± 7.29

0.375

0.557

0.283

slof_work

1st

71

22.85 ± 4.76

69

22.17 ± 4.76

0.405

0.270

slof_work

2nd

28

22.50 ± 3.94

0.138

26

22.29 ± 3.91

-0.047

0.844

0.084

slof_relationship

1st

71

24.90 ± 5.97

69

25.51 ± 5.97

0.549

-0.196

slof_relationship

2nd

28

24.03 ± 4.92

0.283

26

26.30 ± 4.89

-0.255

0.091

-0.734

satisfaction

1st

71

19.99 ± 7.26

69

21.19 ± 7.26

0.329

-0.292

satisfaction

2nd

28

20.53 ± 6.20

-0.133

26

22.32 ± 6.16

-0.274

0.291

-0.432

mhc_emotional

1st

71

10.69 ± 3.79

69

11.20 ± 3.79

0.425

-0.267

mhc_emotional

2nd

28

10.97 ± 3.10

-0.143

26

11.38 ± 3.08

-0.095

0.619

-0.218

mhc_social

1st

71

14.75 ± 5.75

69

15.42 ± 5.75

0.489

-0.201

mhc_social

2nd

28

15.39 ± 4.96

-0.192

26

15.66 ± 4.93

-0.071

0.843

-0.080

mhc_psychological

1st

71

21.80 ± 6.69

69

22.09 ± 6.69

0.802

-0.074

mhc_psychological

2nd

28

22.24 ± 5.72

-0.115

26

22.80 ± 5.69

-0.187

0.719

-0.146

resilisnce

1st

71

16.25 ± 4.63

69

17.13 ± 4.63

0.264

-0.319

resilisnce

2nd

28

16.36 ± 4.02

-0.039

26

18.73 ± 4.00

-0.580

0.032

-0.860

social_provision

1st

71

13.11 ± 2.89

69

14.03 ± 2.89

0.063

-0.502

social_provision

2nd

28

12.59 ± 2.57

0.287

26

14.20 ± 2.56

-0.095

0.022

-0.885

els_value_living

1st

71

16.59 ± 3.19

69

17.35 ± 3.19

0.163

-0.406

els_value_living

2nd

28

16.84 ± 2.75

-0.131

26

17.87 ± 2.74

-0.283

0.166

-0.558

els_life_fulfill

1st

71

12.37 ± 3.39

69

13.14 ± 3.39

0.176

-0.501

els_life_fulfill

2nd

28

12.84 ± 2.68

-0.304

26

13.49 ± 2.66

-0.224

0.369

-0.421

els

1st

71

28.96 ± 6.01

69

30.49 ± 6.01

0.133

-0.543

els

2nd

28

29.66 ± 4.79

-0.248

26

31.35 ± 4.75

-0.304

0.194

-0.600

social_connect

1st

71

26.73 ± 9.61

69

26.19 ± 9.61

0.738

0.118

social_connect

2nd

28

27.90 ± 7.72

-0.253

26

23.67 ± 7.66

0.545

0.044

0.916

shs_agency

1st

71

13.97 ± 5.16

69

14.77 ± 5.16

0.362

-0.308

shs_agency

2nd

28

14.06 ± 4.20

-0.034

26

15.64 ± 4.17

-0.338

0.166

-0.613

shs_pathway

1st

71

15.75 ± 4.02

69

16.39 ± 4.02

0.344

-0.321

shs_pathway

2nd

28

15.98 ± 3.27

-0.116

26

16.55 ± 3.25

-0.081

0.519

-0.286

shs

1st

71

29.72 ± 8.76

69

31.16 ± 8.76

0.332

-0.344

shs

2nd

28

30.04 ± 7.03

-0.077

26

32.18 ± 6.97

-0.243

0.264

-0.509

esteem

1st

71

12.65 ± 1.56

69

12.58 ± 1.56

0.796

0.056

esteem

2nd

28

12.67 ± 1.50

-0.020

26

12.75 ± 1.50

-0.142

0.844

-0.066

mlq_search

1st

71

14.70 ± 3.48

69

14.97 ± 3.48

0.651

-0.113

mlq_search

2nd

28

14.90 ± 3.17

-0.085

26

14.93 ± 3.16

0.019

0.978

-0.010

mlq_presence

1st

71

13.38 ± 4.19

69

13.65 ± 4.19

0.701

-0.111

mlq_presence

2nd

28

13.59 ± 3.61

-0.086

26

13.94 ± 3.59

-0.120

0.718

-0.145

mlq

1st

71

28.08 ± 6.94

69

28.62 ± 6.94

0.647

-0.127

mlq

2nd

28

28.51 ± 6.08

-0.100

26

28.89 ± 6.05

-0.064

0.815

-0.092

empower

1st

71

18.97 ± 4.28

69

19.61 ± 4.28

0.380

-0.304

empower

2nd

28

19.22 ± 3.46

-0.117

26

19.34 ± 3.43

0.128

0.895

-0.059

ismi_resistance

1st

71

14.48 ± 2.50

69

14.62 ± 2.50

0.733

-0.081

ismi_resistance

2nd

28

14.42 ± 2.32

0.034

26

15.10 ± 2.32

-0.268

0.282

-0.383

ismi_discrimation

1st

71

11.96 ± 3.16

69

11.22 ± 3.16

0.168

0.419

ismi_discrimation

2nd

28

11.65 ± 2.68

0.172

26

11.14 ± 2.66

0.044

0.481

0.291

sss_affective

1st

71

10.03 ± 3.50

69

9.81 ± 3.50

0.715

0.114

sss_affective

2nd

28

10.17 ± 2.94

-0.073

26

8.76 ± 2.92

0.553

0.079

0.740

sss_behavior

1st

71

9.89 ± 3.72

69

9.43 ± 3.72

0.472

0.220

sss_behavior

2nd

28

9.87 ± 3.14

0.006

26

8.70 ± 3.12

0.359

0.168

0.573

sss_cognitive

1st

71

8.24 ± 3.70

69

8.14 ± 3.70

0.880

0.047

sss_cognitive

2nd

28

8.92 ± 3.11

-0.338

26

7.45 ± 3.09

0.345

0.083

0.731

sss

1st

71

28.15 ± 10.13

69

27.39 ± 10.13

0.656

0.152

sss

2nd

28

28.89 ± 8.22

-0.146

26

25.01 ± 8.16

0.473

0.084

0.771

Between group

recovery_stage_a

1st

t(180.09) = -0.70, p = 0.486, Cohen d = 0.14, 95% CI (-0.52 to 0.25)

2st

t(177.14) = 1.15, p = 0.253, Cohen d = -0.37, 95% CI (-0.26 to 0.96)

recovery_stage_b

1st

t(174.03) = 0.29, p = 0.770, Cohen d = -0.07, 95% CI (-0.81 to 1.10)

2st

t(171.95) = 1.27, p = 0.205, Cohen d = -0.43, 95% CI (-0.52 to 2.41)

ras_confidence

1st

t(156.28) = 0.45, p = 0.650, Cohen d = -0.14, 95% CI (-1.34 to 2.14)

2st

t(173.80) = 1.27, p = 0.205, Cohen d = -0.53, 95% CI (-0.84 to 3.88)

ras_willingness

1st

t(156.79) = 0.75, p = 0.455, Cohen d = -0.23, 95% CI (-0.43 to 0.97)

2st

t(173.25) = 1.98, p = 0.050, Cohen d = -0.81, 95% CI (0.00 to 1.91)

ras_goal

1st

t(160.70) = 0.93, p = 0.354, Cohen d = -0.26, 95% CI (-0.56 to 1.55)

2st

t(170.20) = 2.74, p = 0.007, Cohen d = -1.07, 95% CI (0.57 to 3.55)

ras_reliance

1st

t(154.57) = 0.88, p = 0.382, Cohen d = -0.28, 95% CI (-0.54 to 1.41)

2st

t(175.91) = 2.24, p = 0.027, Cohen d = -0.95, 95% CI (0.17 to 2.78)

ras_domination

1st

t(169.77) = -1.25, p = 0.212, Cohen d = 0.30, 95% CI (-1.29 to 0.29)

2st

t(169.74) = 1.53, p = 0.128, Cohen d = -0.54, 95% CI (-0.27 to 2.11)

symptom

1st

t(147.99) = 0.01, p = 0.994, Cohen d = -0.00, 95% CI (-3.15 to 3.17)

2st

t(184.70) = -0.59, p = 0.557, Cohen d = 0.28, 95% CI (-5.10 to 2.76)

slof_work

1st

t(154.09) = -0.83, p = 0.405, Cohen d = 0.27, 95% CI (-2.26 to 0.92)

2st

t(176.60) = -0.20, p = 0.844, Cohen d = 0.08, 95% CI (-2.32 to 1.90)

slof_relationship

1st

t(153.74) = 0.60, p = 0.549, Cohen d = -0.20, 95% CI (-1.39 to 2.60)

2st

t(177.10) = 1.70, p = 0.091, Cohen d = -0.73, 95% CI (-0.37 to 4.90)

satisfaction

1st

t(157.28) = 0.98, p = 0.329, Cohen d = -0.29, 95% CI (-1.22 to 3.63)

2st

t(172.76) = 1.06, p = 0.291, Cohen d = -0.43, 95% CI (-1.54 to 5.10)

mhc_emotional

1st

t(152.96) = 0.80, p = 0.425, Cohen d = -0.27, 95% CI (-0.75 to 1.78)

2st

t(178.29) = 0.50, p = 0.619, Cohen d = -0.22, 95% CI (-1.24 to 2.08)

mhc_social

1st

t(158.45) = 0.69, p = 0.489, Cohen d = -0.20, 95% CI (-1.25 to 2.59)

2st

t(171.71) = 0.20, p = 0.843, Cohen d = -0.08, 95% CI (-2.39 to 2.92)

mhc_psychological

1st

t(157.52) = 0.25, p = 0.802, Cohen d = -0.07, 95% CI (-1.95 to 2.52)

2st

t(172.52) = 0.36, p = 0.719, Cohen d = -0.15, 95% CI (-2.51 to 3.63)

resilisnce

1st

t(159.33) = 1.12, p = 0.264, Cohen d = -0.32, 95% CI (-0.67 to 2.42)

2st

t(171.04) = 2.17, p = 0.032, Cohen d = -0.86, 95% CI (0.21 to 4.52)

social_provision

1st

t(162.33) = 1.87, p = 0.063, Cohen d = -0.50, 95% CI (-0.05 to 1.88)

2st

t(169.49) = 2.31, p = 0.022, Cohen d = -0.88, 95% CI (0.24 to 2.99)

els_value_living

1st

t(158.48) = 1.40, p = 0.163, Cohen d = -0.41, 95% CI (-0.31 to 1.82)

2st

t(171.68) = 1.39, p = 0.166, Cohen d = -0.56, 95% CI (-0.44 to 2.51)

els_life_fulfill

1st

t(150.01) = 1.36, p = 0.176, Cohen d = -0.50, 95% CI (-0.35 to 1.91)

2st

t(183.36) = 0.90, p = 0.369, Cohen d = -0.42, 95% CI (-0.78 to 2.09)

els

1st

t(150.72) = 1.51, p = 0.133, Cohen d = -0.54, 95% CI (-0.47 to 3.54)

2st

t(182.09) = 1.30, p = 0.194, Cohen d = -0.60, 95% CI (-0.87 to 4.26)

social_connect

1st

t(151.40) = -0.33, p = 0.738, Cohen d = 0.12, 95% CI (-3.75 to 2.67)

2st

t(180.89) = -2.02, p = 0.044, Cohen d = 0.92, 95% CI (-8.37 to -0.11)

shs_agency

1st

t(152.68) = 0.91, p = 0.362, Cohen d = -0.31, 95% CI (-0.93 to 2.52)

2st

t(178.73) = 1.39, p = 0.166, Cohen d = -0.61, 95% CI (-0.67 to 3.84)

shs_pathway

1st

t(152.55) = 0.95, p = 0.344, Cohen d = -0.32, 95% CI (-0.70 to 1.99)

2st

t(178.95) = 0.65, p = 0.519, Cohen d = -0.29, 95% CI (-1.18 to 2.32)

shs

1st

t(151.21) = 0.97, p = 0.332, Cohen d = -0.34, 95% CI (-1.49 to 4.37)

2st

t(181.22) = 1.12, p = 0.264, Cohen d = -0.51, 95% CI (-1.62 to 5.89)

esteem

1st

t(176.51) = -0.26, p = 0.796, Cohen d = 0.06, 95% CI (-0.59 to 0.45)

2st

t(173.81) = 0.20, p = 0.844, Cohen d = -0.07, 95% CI (-0.72 to 0.88)

mlq_search

1st

t(166.32) = 0.45, p = 0.651, Cohen d = -0.11, 95% CI (-0.89 to 1.43)

2st

t(168.99) = 0.03, p = 0.978, Cohen d = -0.01, 95% CI (-1.68 to 1.73)

mlq_presence

1st

t(158.45) = 0.38, p = 0.701, Cohen d = -0.11, 95% CI (-1.13 to 1.67)

2st

t(171.70) = 0.36, p = 0.718, Cohen d = -0.14, 95% CI (-1.58 to 2.29)

mlq

1st

t(160.53) = 0.46, p = 0.647, Cohen d = -0.13, 95% CI (-1.78 to 2.85)

2st

t(170.29) = 0.23, p = 0.815, Cohen d = -0.09, 95% CI (-2.87 to 3.65)

empower

1st

t(151.87) = 0.88, p = 0.380, Cohen d = -0.30, 95% CI (-0.79 to 2.07)

2st

t(180.08) = 0.13, p = 0.895, Cohen d = -0.06, 95% CI (-1.73 to 1.97)

ismi_resistance

1st

t(169.79) = 0.34, p = 0.733, Cohen d = -0.08, 95% CI (-0.69 to 0.98)

2st

t(169.75) = 1.08, p = 0.282, Cohen d = -0.38, 95% CI (-0.57 to 1.93)

ismi_discrimation

1st

t(156.62) = -1.39, p = 0.168, Cohen d = 0.42, 95% CI (-1.80 to 0.31)

2st

t(173.42) = -0.71, p = 0.481, Cohen d = 0.29, 95% CI (-1.95 to 0.92)

sss_affective

1st

t(155.47) = -0.37, p = 0.715, Cohen d = 0.11, 95% CI (-1.39 to 0.95)

2st

t(174.76) = -1.77, p = 0.079, Cohen d = 0.74, 95% CI (-2.98 to 0.17)

sss_behavior

1st

t(156.23) = -0.72, p = 0.472, Cohen d = 0.22, 95% CI (-1.69 to 0.79)

2st

t(173.86) = -1.38, p = 0.168, Cohen d = 0.57, 95% CI (-2.86 to 0.50)

sss_cognitive

1st

t(155.43) = -0.15, p = 0.880, Cohen d = 0.05, 95% CI (-1.33 to 1.14)

2st

t(174.80) = -1.74, p = 0.083, Cohen d = 0.73, 95% CI (-3.13 to 0.20)

sss

1st

t(152.30) = -0.45, p = 0.656, Cohen d = 0.15, 95% CI (-4.15 to 2.62)

2st

t(179.35) = -1.74, p = 0.084, Cohen d = 0.77, 95% CI (-8.28 to 0.53)

Within treatment group

recovery_stage_a

1st vs 2st

t(90.53) = 2.07, p = 0.083, Cohen d = -0.51, 95% CI (0.02 to 0.96)

recovery_stage_b

1st vs 2st

t(82.12) = 0.77, p = 0.884, Cohen d = -0.20, 95% CI (-0.67 to 1.52)

ras_confidence

1st vs 2st

t(64.82) = 2.37, p = 0.041, Cohen d = -0.63, 95% CI (0.29 to 3.35)

ras_willingness

1st vs 2st

t(65.23) = 0.68, p = 1.000, Cohen d = -0.18, 95% CI (-0.41 to 0.83)

ras_goal

1st vs 2st

t(68.51) = 2.18, p = 0.065, Cohen d = -0.57, 95% CI (0.10 to 2.12)

ras_reliance

1st vs 2st

t(63.48) = 3.34, p = 0.003, Cohen d = -0.89, 95% CI (0.55 to 2.21)

ras_domination

1st vs 2st

t(77.23) = 2.55, p = 0.025, Cohen d = -0.65, 95% CI (0.24 to 1.97)

symptom

1st vs 2st

t(59.24) = -1.39, p = 0.340, Cohen d = 0.37, 95% CI (-3.78 to 0.68)

slof_work

1st vs 2st

t(63.10) = 0.18, p = 1.000, Cohen d = -0.05, 95% CI (-1.21 to 1.44)

slof_relationship

1st vs 2st

t(62.83) = 0.96, p = 0.685, Cohen d = -0.25, 95% CI (-0.86 to 2.43)

satisfaction

1st vs 2st

t(65.63) = 1.04, p = 0.609, Cohen d = -0.27, 95% CI (-1.05 to 3.31)

mhc_emotional

1st vs 2st

t(62.24) = 0.35, p = 1.000, Cohen d = -0.09, 95% CI (-0.84 to 1.21)

mhc_social

1st vs 2st

t(66.59) = 0.27, p = 1.000, Cohen d = -0.07, 95% CI (-1.53 to 2.00)

mhc_psychological

1st vs 2st

t(65.82) = 0.71, p = 0.965, Cohen d = -0.19, 95% CI (-1.30 to 2.73)

resilisnce

1st vs 2st

t(67.33) = 2.21, p = 0.062, Cohen d = -0.58, 95% CI (0.15 to 3.04)

social_provision

1st vs 2st

t(69.95) = 0.36, p = 1.000, Cohen d = -0.09, 95% CI (-0.78 to 1.12)

els_value_living

1st vs 2st

t(66.62) = 1.07, p = 0.575, Cohen d = -0.28, 95% CI (-0.45 to 1.51)

els_life_fulfill

1st vs 2st

t(60.05) = 0.83, p = 0.818, Cohen d = -0.22, 95% CI (-0.49 to 1.18)

els

1st vs 2st

t(60.57) = 1.13, p = 0.524, Cohen d = -0.30, 95% CI (-0.66 to 2.38)

social_connect

1st vs 2st

t(61.07) = -2.03, p = 0.093, Cohen d = 0.55, 95% CI (-5.00 to -0.04)

shs_agency

1st vs 2st

t(62.03) = 1.27, p = 0.421, Cohen d = -0.34, 95% CI (-0.51 to 2.26)

shs_pathway

1st vs 2st

t(61.93) = 0.30, p = 1.000, Cohen d = -0.08, 95% CI (-0.91 to 1.23)

shs

1st vs 2st

t(60.93) = 0.91, p = 0.738, Cohen d = -0.24, 95% CI (-1.23 to 3.27)

esteem

1st vs 2st

t(85.30) = 0.56, p = 1.000, Cohen d = -0.14, 95% CI (-0.44 to 0.78)

mlq_search

1st vs 2st

t(73.69) = -0.07, p = 1.000, Cohen d = 0.02, 95% CI (-1.26 to 1.17)

mlq_presence

1st vs 2st

t(66.60) = 0.45, p = 1.000, Cohen d = -0.12, 95% CI (-0.99 to 1.58)

mlq

1st vs 2st

t(68.36) = 0.24, p = 1.000, Cohen d = -0.06, 95% CI (-1.94 to 2.48)

empower

1st vs 2st

t(61.42) = -0.48, p = 1.000, Cohen d = 0.13, 95% CI (-1.39 to 0.85)

ismi_resistance

1st vs 2st

t(77.25) = 1.05, p = 0.597, Cohen d = -0.27, 95% CI (-0.43 to 1.39)

ismi_discrimation

1st vs 2st

t(65.10) = -0.17, p = 1.000, Cohen d = 0.04, 95% CI (-1.01 to 0.86)

sss_affective

1st vs 2st

t(64.18) = -2.08, p = 0.082, Cohen d = 0.55, 95% CI (-2.06 to -0.04)

sss_behavior

1st vs 2st

t(64.78) = -1.36, p = 0.360, Cohen d = 0.36, 95% CI (-1.83 to 0.35)

sss_cognitive

1st vs 2st

t(64.15) = -1.30, p = 0.396, Cohen d = 0.35, 95% CI (-1.76 to 0.37)

sss

1st vs 2st

t(61.74) = -1.77, p = 0.164, Cohen d = 0.47, 95% CI (-5.07 to 0.31)

Within control group

recovery_stage_a

1st vs 2st

t(89.05) = -0.00, p = 1.000, Cohen d = 0.00, 95% CI (-0.46 to 0.46)

recovery_stage_b

1st vs 2st

t(81.01) = -0.71, p = 0.960, Cohen d = 0.17, 95% CI (-1.44 to 0.68)

ras_confidence

1st vs 2st

t(64.41) = 0.94, p = 0.701, Cohen d = -0.24, 95% CI (-0.78 to 2.17)

ras_willingness

1st vs 2st

t(64.80) = -1.60, p = 0.231, Cohen d = 0.41, 95% CI (-1.08 to 0.12)

ras_goal

1st vs 2st

t(67.95) = -0.94, p = 0.702, Cohen d = 0.24, 95% CI (-1.44 to 0.52)

ras_reliance

1st vs 2st

t(63.11) = 0.84, p = 0.807, Cohen d = -0.22, 95% CI (-0.46 to 1.13)

ras_domination

1st vs 2st

t(76.32) = -0.75, p = 0.911, Cohen d = 0.19, 95% CI (-1.15 to 0.52)

symptom

1st vs 2st

t(59.09) = -0.34, p = 1.000, Cohen d = 0.09, 95% CI (-2.52 to 1.79)

slof_work

1st vs 2st

t(62.74) = -0.54, p = 1.000, Cohen d = 0.14, 95% CI (-1.62 to 0.93)

slof_relationship

1st vs 2st

t(62.49) = -1.10, p = 0.550, Cohen d = 0.28, 95% CI (-2.46 to 0.71)

satisfaction

1st vs 2st

t(65.18) = 0.52, p = 1.000, Cohen d = -0.13, 95% CI (-1.55 to 2.65)

mhc_emotional

1st vs 2st

t(61.91) = 0.56, p = 1.000, Cohen d = -0.14, 95% CI (-0.71 to 1.26)

mhc_social

1st vs 2st

t(66.11) = 0.75, p = 0.906, Cohen d = -0.19, 95% CI (-1.06 to 2.35)

mhc_psychological

1st vs 2st

t(65.37) = 0.45, p = 1.000, Cohen d = -0.11, 95% CI (-1.51 to 2.38)

resilisnce

1st vs 2st

t(66.82) = 0.15, p = 1.000, Cohen d = -0.04, 95% CI (-1.29 to 1.50)

social_provision

1st vs 2st

t(69.34) = -1.14, p = 0.517, Cohen d = 0.29, 95% CI (-1.44 to 0.39)

els_value_living

1st vs 2st

t(66.14) = 0.51, p = 1.000, Cohen d = -0.13, 95% CI (-0.70 to 1.19)

els_life_fulfill

1st vs 2st

t(59.80) = 1.17, p = 0.492, Cohen d = -0.30, 95% CI (-0.33 to 1.28)

els

1st vs 2st

t(60.30) = 0.96, p = 0.685, Cohen d = -0.25, 95% CI (-0.76 to 2.16)

social_connect

1st vs 2st

t(60.78) = 0.98, p = 0.663, Cohen d = -0.25, 95% CI (-1.22 to 3.56)

shs_agency

1st vs 2st

t(61.71) = 0.13, p = 1.000, Cohen d = -0.03, 95% CI (-1.25 to 1.42)

shs_pathway

1st vs 2st

t(61.61) = 0.45, p = 1.000, Cohen d = -0.12, 95% CI (-0.80 to 1.27)

shs

1st vs 2st

t(60.65) = 0.30, p = 1.000, Cohen d = -0.08, 95% CI (-1.85 to 2.49)

esteem

1st vs 2st

t(84.05) = 0.08, p = 1.000, Cohen d = -0.02, 95% CI (-0.56 to 0.61)

mlq_search

1st vs 2st

t(72.93) = 0.34, p = 1.000, Cohen d = -0.08, 95% CI (-0.97 to 1.37)

mlq_presence

1st vs 2st

t(66.11) = 0.34, p = 1.000, Cohen d = -0.09, 95% CI (-1.03 to 1.45)

mlq

1st vs 2st

t(67.81) = 0.39, p = 1.000, Cohen d = -0.10, 95% CI (-1.71 to 2.56)

empower

1st vs 2st

t(61.12) = 0.45, p = 1.000, Cohen d = -0.12, 95% CI (-0.84 to 1.33)

ismi_resistance

1st vs 2st

t(76.35) = -0.14, p = 1.000, Cohen d = 0.03, 95% CI (-0.94 to 0.82)

ismi_discrimation

1st vs 2st

t(64.67) = -0.67, p = 1.000, Cohen d = 0.17, 95% CI (-1.20 to 0.60)

sss_affective

1st vs 2st

t(63.78) = 0.29, p = 1.000, Cohen d = -0.07, 95% CI (-0.83 to 1.11)

sss_behavior

1st vs 2st

t(64.36) = -0.02, p = 1.000, Cohen d = 0.01, 95% CI (-1.06 to 1.04)

sss_cognitive

1st vs 2st

t(63.76) = 1.32, p = 0.383, Cohen d = -0.34, 95% CI (-0.35 to 1.71)

sss

1st vs 2st

t(61.43) = 0.56, p = 1.000, Cohen d = -0.15, 95% CI (-1.86 to 3.32)

Plot

Clinical significance